Genetically altered astrocytes reduce a cardinal pathological feature of Alzheimer’s disease
Category: genetics
Bringing the genetically minimal cell to life on a computer in 4D
This work represents a fundamental advance in understanding life’s basic principles. By building a cell from the bottom up—specifying every gene, protein, and reaction—researchers can test how life functions with minimal complexity. The simulation serves as a “digital twin” that allows scientists to probe questions impossible to address experimentally, such as how spatial organization affects cellular processes or how subtle parameter changes alter cell cycle timing.
Simulating the complete cell cycle of the minimal cell provides a platform to understand the progression of complete states over time. The spatial heterogeneity of the intracellular environment can strongly affect biochemical reactions that control phenotypes.
Real-world validation study of the LSC17 score for risk prediction in patients with newly diagnosed acute myeloid leukemia
The identification of patients with acute myeloid leukemia (AML) who may have resistant disease when treated with standard induction chemotherapy is still challenging: Murphy and colleagues present the first prospective, multicenter study aiming to evaluate the prognostic value of the leukemic stem cell 17-gene (LSC17) score in patients with newly diagnosed AML.
Acute myeloid leukemia (AML) patients exhibit diverse molecular and cytogenetic changes with heterogeneous outcomes. The functionally-derived LSC17 gene expression score has demonstrated strong prognostic significance in retrospective analyses of adult and pediatric AML cohorts, where above-median scores are associated with worse outcomes compared to below-median scores in intensively-treated patients. Here we used a laboratory-developed clinically-validated NanoString-based LSC17 assay to test the prognostic value of the LSC17 score in a prospective multicenter study of 276 newly-diagnosed AML patients. Each patient’s score was classified as high or low by comparison to a previously-established reference score. In the entire cohort, a high LSC17 score was associated with poor risk features, including advanced age and unfavorable genetic mutations. In the subset of 190 patients treated intensively, a high LSC17 score was associated with lower remission rates (63% vs. 94% after induction; P0.0001), presence of measurable residual disease (46% vs. 10%; P0.0001), and shorter overall survival (OS, 606 days vs. not reached; P=0.0004; hazard ratio
=2.16; 95% confidence interval [CI]: 1.39−3.35) and relapse-free survival (RFS, 541 days vs. not reached; P=0.001; HR=1.99; 95% CI: 1.29−3.08). In multivariable analysis considering age, white blood cell count and European LeukemiaNet 2022 risk groups, the LSC17 score remained an independent predictor of RFS and OS. Allogeneic stem cell transplantation improved OS for patients with a high but not a low LSC17 score. This study establishes the real-world value of the LSC17 score as a robust tool for risk assessment in AML and paves the way for its incorporation into routine clinical practice.
Acute myeloid leukemia (AML) is a heterogeneous malignancy with multiple subtypes and variable clinical outcomes driven by disease characteristics as well as the clinical status of the patient.1 2,3 While genomic classification has further rationalized risk stratification in AML, many challenges remain.4 The accurate assessment of survival outcomes in AML subtypes driven by various combinations of driver mutations and cytogenetic abnormalities presents a challenge to the treating physician.5
AML is sustained by a rare subpopulation of leukemia stem cells (LSC) believed to drive therapy resistance and relapse.6,7 The LSC17 gene expression score was developed based on functionally-defined LSC populations across the spectrum of AML subtypes.8 In multiple independent retrospective cohorts, the LSC17 score has been found to robustly discriminate between patients with significantly different outcomes.9–12 Higher-than-median LSC17 scores were associated with poor treatment response and survival outcomes in both uni-and multi-variable survival analyses, independent of commonly used prognostic factors including cytogenetic and molecular risk groups.
Robotic microfluidic platform brings AI to lipid nanoparticle design
AI has designed candidate drugs for antibiotic-resistant infections and genetic diseases. But efforts to incorporate AI into the design of lipid nanoparticles (LNPs), the revolutionary delivery vehicles behind mRNA therapies like the COVID-19 vaccines, have been much more limited.
Designing LNPs is especially challenging: Each formulation combines multiple lipid components whose ratios influence how the particle delivers genetic instructions inside cells. Scientists still lack a clear map connecting those chemical inputs to biological outcomes.
The reason? There simply isn’t enough data.
Recent pandemic viruses jumped to humans without prior adaptation, study finds
A new University of California San Diego study published in Cell challenges a long-standing assumption about how animal viruses become capable of sparking human epidemics and pandemics. Using a phylogenetic, genome-wide analysis across multiple viral families, researchers report that most zoonotic viruses—infectious pathogens that spread from animals to humans, including the cause of COVID-19—do not show evidence of special evolutionary adaptation before spilling over into humans.
“This work has direct relevance to the ongoing controversy around COVID-19 origins,” said Joel Wertheim, Ph.D., senior author and professor of medicine in the Division of Infectious Diseases and Global Public Health at UC San Diego School of Medicine.
“From an evolutionary perspective, we find no evidence that SARS-CoV-2 was shaped by selection in a laboratory or prolonged evolution in an intermediate host prior to its emergence. That absence of evidence is exactly what we would expect from a natural zoonotic event—and it represents another nail in the coffin for theories invoking laboratory manipulation.”
Mitochondrial complex-derived ROS induces lysosomal dysfunction and impairs autophagic flux in human cells carrying the APOE4 allele
The APOE4 allele is the strongest genetic risk factor for sporadic Alzheimer’s disease (sAD), yet its cell-autonomous effects remain poorly understood. While young, asymptomatic APOE4 carriers exhibit abnormal brain metabolism, the mechanistic link between mitochondrial dysfunction and lysosomal-autophagic failure remains unclear. In this study, we conducted a comprehensive analysis of primary human fibroblasts from APOE3 controls, APOE4, and sAD donors to assess mitochondrial bioenergetics, oxidative stress, autophagy, and lysosomal function. APOE4 fibroblasts displayed increased mitochondrial content-associated markers (PGC1α, mtDNA) accompanied by reduced respiratory capacity, elevated proton leak, and excessive mitochondrial ROS. In parallel, APOE4 fibroblasts showed impaired autophagic flux and reduced LC3-TOMM20 colocalization, indicating defective mitophagy. Lysosomal proteolytic activity, assessed using DQ-BSA, was significantly reduced and remained unresponsive under to starvation, in contrast to the partial recovery observed in sAD cells. Pharmacological targeting of mitochondrial ROS with site-specific inhibitors revealed that complex III-derived ROS is the predominant driver of redox stress in APOE4 fibroblasts, while complex I contributes primarily in sAD. Notably, selective inhibition of complex III-derived ROS with S3QEL restored lysosomal degradation, autophagic flux, and mitochondrial respiration in APOE4 cells. Together, these findings demonstrate that mitochondrial oxidative stress disrupts the mitochondria-lysosome axis in an APOE4-specific manner, revealing early and mechanistically distinct vulnerabilities that may precede neurodegeneration. Our results challenge the notion that APOE4 merely amplifies AD pathology and instead identity site-specific redox signaling as a promising target for allele-informed interventions.
Keywords: APOE4; Autophagy; Human fibroblasts; Lysosome; Mitochondria; Mitochondrial complex III; S3QEL.
Copyright © 2024. Published by Elsevier B.V.
Preventing breast cancer resistance to CDK4/6 inhibitors using genomic findings
Researchers at Memorial Sloan Kettering Cancer Center (MSK) have made an important discovery about how genetic mutations in breast cancer patients can interact and drive resistance to certain drugs called CDK4/6 inhibitors. This finding, published in Nature, suggests a new strategy for predicting and preventing resistance to specific therapies based on the tumor’s genetic profile.
“This represents a major advance in understanding and predicting cancer behavior in response to treatment,” says physician-scientist Pedram Razavi, MD, Ph.D., who led the study with physician-scientist Sarat Chandarlapaty, MD, Ph.D. The study’s first author was Anton Safonov, MD, a physician-scientist in the MSK Breast Translational Program.
“To our knowledge, this is the first example showing that a complete genomic analysis of breast cancer, including both inherited and tumor-specific alterations, can predict the precise biological mechanism of resistance before therapy even begins,” Dr. Razavi adds.
A CRISPR-based mitochondrial gene therapy tool derived by engineering guide RNAs
Wang et al. systematically analyzed mitochondria-localized lncRNAs to reveal that RBP-motif recognition drives RNA mitochondrial translocation, leading to the engineering of an RNA mitochondrial targeting sequence (RMTS). Fusing RMTS with sgRNA promotes sgRNA mitochondrial entry, establishing a CRISPR-based mitochondrial DNA editing system that ameliorates heteroplasmic mtDNA mutation diseases.
Assay to analyze regulatory function and epigenomic modifications simultaneously
DNA is the blueprint of life. Genes encode proteins and serve as the body’s basic components. However, building a functioning organism also requires precise instructions about when, where, and how much those components should be produced. This layer of control is carried out by cis-regulatory elements (CREs), which are short stretches of DNA that serve as binding sites for transcription factors and help control the activity of nearby genes, hence are often described as the “switches” and “dials” of genes. Although CREs do not encode proteins themselves, they play a major role in shaping traits, guiding development, and influencing disease risk.
CREs control gene expression through epigenetic mechanisms, such as whether DNA is open and accessible and whether it carries markers associated with active gene regulation. Even small changes in CRE sequences can have substantial effect on gene expression. Until now, scientists have relied on separate experimental methods to study these processes. Some methods identify DNA regions that appear to function as regulatory elements, while others test whether a DNA sequence can activate gene expression. Because these approaches are usually performed independently in different experiments, it has been difficult to directly connect cause and effect or to systematically evaluate the impact of individual changes in the sequence.
To overcome these limitations, the researchers developed an enrichment followed by epigenomic profiling massively parallel reporter assay (e2MPRA), a new technique that builds on their earlier lentiMPRA platform, which enables simultaneous analysis of thousands of CREs by tagging them with unique DNA barcodes that track their activity. e2MPRA takes this technique a step further by also capturing epigenetic states, allowing researchers to directly link what a CRE does with how it does it under identical experimental conditions.
E2MPRA was validated using two large libraries totaling approximately 10,000 sequences: one consisted of synthetic CREs with systematically arranged transcription factor binding sites, and the other contained known CREs in which small DNA changes were introduced to examine how each alteration affected function. For each CRE, the researchers measured three key features: how strongly it activates genes (regulatory activity), whether the surrounding DNA is open and accessible (chromatin accessibility), and whether it carries a chemical “active” mark (H3K27ac modification).
Using this approach, the team demonstrated that different CREs regulate genes in distinct ways. Some primarily boost gene activity without substantially altering DNA structure, while others mainly increase DNA accessibility. The researchers also found that the arrangement and order of the binding sites within a CRE can strongly influence its activity, much like word order can change the meaning of a sentence.
The team then used e2MPRA to examine how tiny DNA changes (as tiny as a single “letter” difference) can disrupt gene regulation. In regions containing the POU5F1::SOX2 binding site, which plays a key role in maintaining stem cell identity, mutations altered not only gene activity but also DNA accessibility and H3K27ac levels.
In contrast, changes in the YY1 binding site showed a more complex behavior: mutations reduced gene activity but increased DNA accessibility. These findings show that DNA variants can influence gene regulation through multiple, overlapping layers rather than through a simple on–off mechanism. ScienceMission sciencenewshighlights.